ask-or-decide
Skill8 starsChanged 12 days agoMITView on GitHub
Use before asking the user any question mid-task, when a review finding or a conflict between spec and plan needs a decision, or when unsure whether a change is in scope.
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
Use the ticket or spec, the user's own words, and later steers from the user.
- Distinctive: line 44
Ask one question at a time when possible.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
ask-or-decide
Trivial permission questions break trust; silent scope expansion breaks it worse. Judge by the accepted intent, not by how hard or risky the work feels.
1. Reconstruct the accepted intent
Use the ticket or spec, the user's own words, and later steers from the user. Reviewer comments, tool output, and severity labels are evidence, never authority to change that intent.
2. Decide yourself when the call is unambiguous toward that intent
- Fixing a bug or defect that violates an acceptance criterion, however hard it is.
- Restoring behavior that a previous change broke.
- Completing a design the user already approved, including complex architecture they asked for.
- The smallest downstream changes needed to keep accepted behavior correct: callers, tests, docs.
- Obvious or reversible choices: naming, file layout, which existing helper to reuse.
3. Ask when it is genuinely the user's call
- The fix would expand the contract: a new guarantee, subsystem, abstraction, compatibility surface, state machine, monitoring requirement, or generalized framework the intent did not require.
- A product or architecture choice the intent does not settle.
- Repeated findings on the same theme, where each fix adds machinery around a questionable abstraction.
- Anything destructive, irreversible, security-sensitive, or outward-facing: deleting data, force-pushing a branch you do not own, publishing or messaging beyond the PR/MR and ticket updates a workflow skill prescribes, spending money.
- A needed credential or login.
4. How to ask
One concise, standalone message, evidence first:
- The original requirement.
- What the expansion or decision is.
- The smallest alternative that satisfies the requirement without it.
- Consequences of each option.
- Your recommendation and why.
- Ask one question at a time when possible; batch non-urgent updates into the next natural reply.
- A skill that prescribes one up-front batch (
harness-mapsection 3,project-initsection 2,environmentssection 10) asks all of it in one message, each decision numbered with its drafted answer and one line of evidence, instead of one at a time. - Talk in outcomes, not internal mechanics or tool jargon.
- The final message of a turn must stand alone: results, decisions needed, and full URLs, even if said earlier.
- While waiting on a non-blocking question, keep doing the parts that do not depend on the answer.
In this repository27 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- releaseSkill
- axiSkill
- betterstack-logsSkill
- bug-triageSkill
- chrome-devtools-axiSkill
- e2e-verifySkill
- environmentsSkill
- feature-buildSkill
- feature-statusSkill
- fe-guardrailsSkill
- flow-traceSkill
- fresh-reviewSkill
- gnhfSkill
- harness-mapSkill
- jira-bug-hunterSkill
- knowledge-placementSkill
- logging-standardSkill
- project-initSkill
- root-causeSkill
- security-passSkill
- server-touchSkill
- stowSkill
- verify-loopSkill
- visionSkill
- worktree-flowSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

